I selected the Apple Music top 100 playlists from different countries because I was curious to explore the cultural variations in music preferences across regions. By comparing these playlists, I aimed to identify common trends in popular songs as well as uncover unique regional music tastes. I wanted to understand if there were any songs that consistently appeared across multiple playlists, indicating their widespread popularity regardless of geographical boundaries. Additionally, I was interested in observing any distinct patterns or genres that dominated specific countries’ playlists, which could provide insights into the local music scenes and cultural influences.
Suppose I want to find common songs between my playlist, “Good Vibes”, and my friend’s playlist, “New hits”, Using SQL, I can perform an INNER JOIN operation on the song titles from both playlists. The query would look like this:
SELECT song_title
FROM good_vibes
INNER JOIN new_hits ON good_vibes.song_title = new_hits.song_title;
This query would retrieve the song titles that appear in both playlists. SQL queries allow for easy comparison of playlists, enabling me to discover shared music interests and initiate engaging conversations about our favorite tunes.
Plot: Mean Song and Number of Songs by year
The combined plot tells a compelling story about the evolution of
music trends over time. The line plot, mean_song_length,
reveals any trends or patterns in the mean song length over the years.
By examining the line, we can observe whether songs have become shorter
or longer on average. The bar plot, total_songs, showcases
the total count of songs released in each year, providing an overview of
music production volume. Together, these plots enable us to explore the
relationship between song length and song production trends in one
static plot instead of two.
The visualization sparks questions and invites further analysis. Are there any significant deviations from the mean song length trend in specific years? How do different genres contribute to these patterns? By encouraging exploration and interpretation, the visualization opens up avenues for deeper investigations into the intricate dynamics of music trends and cultural shifts.